---
title: "BC Socio-economic CEF indicators"
output:
flexdashboard::flex_dashboard:
orientation: columns
source_code: embed
css: custom.css
---
```{r setup, include=FALSE}
library(highcharter)
library(terra)
library(tidyterra)
library(sf)
library(DT)
library(tidyverse)
library(viridisLite)
library(forecast)
library(treemap)
library(arules)
library(geojsonsf)
library(flexdashboard)
thm <-
hc_theme(
colors = c("#042f4b", "#005480", "#a4c1d8", "#85c495"),
chart = list(
backgroundColor = "transparent",
style = list(fontFamily = "Source Sans Pro")
),
xAxis = list(
gridLineWidth = 1
)
)
```
# Page 1
## Inputs {.sidebar}
<div class="sidebar-content">
<!-- Logo -->
<img src="slogo.png" alt="Logo" class="sidebar-logo">
<!-- Sidebar text -->
<p>This is a draft dashboard showing the key CEF socio-economic indicators used in the current condition report.</p>
<!-- Link to external resource -->
<p>In this section we can link our website or the pdf of the report:</p>
[CEF Economic Report](https://www2.gov.bc.ca/gov/content/environment/natural-resource-stewardship/cumulative-effects-framework)
</div>
## Column {.tabset data-width="500"}
### Cariboo
```{r}
data_2015 <- as.data.frame(read_csv("Cariboo_2015.csv"))
data_2020 <- as.data.frame(read_csv("Cariboo_2020.csv"))
# Create the interactive bar chart
highchart() %>%
hc_chart(type = "column") %>%
hc_title(text = "Interactive Bar Chart for 2015 and 2022 Data") %>%
hc_xAxis(categories = data_2015$Sector) %>%
hc_yAxis(title = list(text = "Jobs")) %>%
hc_add_series(name = "Cariboo (2015)", data = data_2015$Jobs, visible = TRUE) %>%
hc_add_series(name = "Cariboo (2020)", data = data_2020$Jobs) %>%
hc_tooltip(valueSuffix = " jobs") %>%
hc_exporting(enabled = TRUE) %>%
hc_chart(events = list(
load = JS("
function() {
var chart = this;
chart.update({
navigation: {
menuItemStyle: {
backgroundColor: '#f7f7f7',
borderColor: '#ccc'
},
buttonStyle: {
backgroundColor: '#2f7ed8',
borderColor: '#2f7ed8'
},
menuItems: [
{
text: 'Show 2015 Data',
onclick: function() {
chart.series[0].setVisible(true);
chart.series[1].setVisible(true);
chart.series[2].setVisible(true);
chart.series[3].setVisible(false);
chart.series[4].setVisible(false);
chart.series[5].setVisible(false);
}
},
{
text: 'Show 2022 Data',
onclick: function() {
chart.series[0].setVisible(false);
chart.series[1].setVisible(false);
chart.series[2].setVisible(false);
chart.series[3].setVisible(true);
chart.series[4].setVisible(true);
chart.series[5].setVisible(true);
}
}
]
}
});
}
")
))
```
### Peace River
```{r}
Peacedata_2015 <- as.data.frame(read_csv("Peace_2015.csv"))
Peacedata_2020 <- as.data.frame(read_csv("Peace_2020.csv"))
# Create the interactive bar chart
highchart() %>%
hc_chart(type = "column") %>%
hc_title(text = "Interactive Bar Chart for 2015 and 2022 Data") %>%
hc_xAxis(categories = Peacedata_2015$Sector) %>%
hc_yAxis(title = list(text = "Jobs")) %>%
hc_add_series(name = "Peace River (2015)", data = Peacedata_2015$Jobs, visible = TRUE) %>%
hc_add_series(name = "Peace River (2020)", data = Peacedata_2020$Jobs) %>%
hc_tooltip(valueSuffix = " jobs") %>%
hc_exporting(enabled = TRUE) %>%
hc_chart(events = list(
load = JS("
function() {
var chart = this;
chart.update({
navigation: {
menuItemStyle: {
backgroundColor: '#f7f7f7',
borderColor: '#ccc'
},
buttonStyle: {
backgroundColor: '#2f7ed8',
borderColor: '#2f7ed8'
},
menuItems: [
{
text: 'Show 2015 Data',
onclick: function() {
chart.series[0].setVisible(true);
chart.series[1].setVisible(true);
chart.series[2].setVisible(true);
chart.series[3].setVisible(false);
chart.series[4].setVisible(false);
chart.series[5].setVisible(false);
}
},
{
text: 'Show 2022 Data',
onclick: function() {
chart.series[0].setVisible(false);
chart.series[1].setVisible(false);
chart.series[2].setVisible(false);
chart.series[3].setVisible(true);
chart.series[4].setVisible(true);
chart.series[5].setVisible(true);
}
}
]
}
});
}
")
))
```
## Column {.tabset data-width="500"}
### Jobs by Region
```{r}
my_data_2020 <- vect("Map_Regeions.gpkg")
my_data_2020 <- as.data.frame(my_data_2020)
geojson2020 <- geojsonio::geojson_read("simple_regions_bc.geojson")
n <- 4
colstops <- data.frame(
q = 0:n/n,
c = substring(viridis(n + 1), 0, 7)) %>%
list_parse2()
highchart() %>%
hc_add_series_map(geojson2020, my_data_2020,
name = "Total Jobs",
value = "Total",
joinBy = c("CENSUS_DIVISION_NAME", "CENSUS_DIVISION_NAME"),
dataLabels = list(enabled = TRUE,
format = '{point.properties.CENSUS_DIVISION_NAME}')) %>%
hc_colorAxis(stops = colstops) %>%
hc_legend(valueDecimals = 0) %>%
hc_mapNavigation(enabled = TRUE)
```
### Test tab by Region
```{r}
my_data_2020 <- vect("Map_Regeions.gpkg")
my_data_2020 <- as.data.frame(my_data_2020)
geojson2020 <- geojsonio::geojson_read("simple_regions_bc.geojson")
n <- 4
colstops <- data.frame(
q = 0:n/n,
c = substring(rainbow(n + 1), 0, 7)) %>%
list_parse2()
highchart() %>%
hc_add_series_map(geojson2020, my_data_2020,
name = "Construction Jobs",
value = "Construction",
joinBy = c("CENSUS_DIVISION_NAME", "CENSUS_DIVISION_NAME"),
dataLabels = list(enabled = TRUE,
format = '{point.properties.CENSUS_DIVISION_NAME}')) %>%
hc_colorAxis(stops = colstops) %>%
hc_legend(valueDecimals = 0) %>%
hc_mapNavigation(enabled = TRUE)
```
# Table Data
## Column {data-width="500"}
### All data
```{r}
DT::datatable(my_data_2020, options = list(
pageLength = 25
))
```